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MCP Server Template for Cursor IDE

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Python
Hybrid

MCP Server Template for Cursor IDE

A simple template for creating custom tools for Cursor IDE using Model Context Protocol (MCP). Create your own repository from this template, modify the tools, and connect them to your Cursor IDE.

Server Mood Response

Quick Start

  1. Click "Deploy to Heroku" button

    Deploy to Heroku

  2. After deployment, configure Cursor:

    • Open Cursor Settings → Features

    • Add new MCP server

    • Use your Heroku URL with /sse path (e.g., https://<your-app-name>.herokuapp.com/sse)

  3. Test your agent's mood in Cursor:

    • Ask your agent "Please ask about our server mood and let me know how it is."

    • The server will respond with a cheerful message and a heart ❤️

Related MCP server: MCP Server Template for Cursor IDE

Alternative Setup Methods

You can run the server in three ways: using Docker, traditional Python setup, or directly in Cursor IDE.

Docker Setup

The project includes Docker support for easy deployment:

  1. Initial setup:

# Clone the repository
git clone https://github.com/kirill-markin/weaviate-mcp-server.git
cd weaviate-mcp-server

# Create environment file
cp .env.example .env

  1. Build and run using Docker Compose:

# Build and start the server
docker compose up --build -d

# View logs
docker compose logs -f

# Check server status
docker compose ps

# Stop the server
docker compose down

  1. The server will be available at:

  2. Quick test:

# Test the server endpoint
curl -i http://localhost:8000/sse

  1. Connect to Cursor IDE:

    • Open Cursor Settings → Features

    • Add new MCP server

    • Type: Select "sse"

    • URL: Enter http://localhost:8000/sse

Traditional Setup

First, install the uv package manager:

# Install uv on macOS
brew install uv
# Or install via pip (any OS)
pip install uv

Start the server using either stdio (default) or SSE transport:

# Install the package with development dependencies
uv pip install -e ".[dev]"

# Using stdio transport (default)
uv run mcp-simple-tool

# Using SSE transport on custom port
uv run mcp-simple-tool --transport sse --port 8000

# Run tests
uv run pytest -v

After installation, you can connect the server directly to Cursor IDE:

  1. Right-click on the cursor-run-mcp-server.sh file in Cursor

  2. Select "Copy Path" to copy the absolute path

  3. Open Cursor Settings (gear icon)

  4. Navigate to Features tab

  5. Scroll down to "MCP Servers"

  6. Click "Add new MCP server"

  7. Fill in the form:

    • Name: Choose any name (e.g., "my-mcp-server-1")

    • Type: Select "stdio" (not "sse" because we run the server locally)

    • Command: Paste the absolute path to cursor-run-mcp-server.sh that you copied earlier. For example: /Users/kirillmarkin/weaviate-mcp-server/cursor-run-mcp-server.sh

Environment Variables

Available environment variables (can be set in .env):

  • MCP_SERVER_PORT (default: 8000) - Port to run the server on

  • MCP_SERVER_HOST (default: 0.0.0.0) - Host to bind the server to

  • DEBUG (default: false) - Enable debug mode

  • MCP_USER_AGENT - Custom User-Agent for website fetching

Additional options

Installing via Smithery

To install MCP Server Template for Cursor IDE for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @kirill-markin/example-mcp-server --client claude

Glama server review

Available Tools

2 tools
mcp_fetchC

Fetches a website and returns its content

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states basic functionality. It doesn't disclose important behavioral traits like error handling, rate limits, authentication needs, content type handling, or what 'returns its content' specifically means (HTML, text, metadata).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise - just 7 words that directly convey the core functionality. Every word earns its place with zero wasted text, making it perfectly front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that fetches websites with no annotations and no output schema, the description is insufficient. It doesn't explain what 'content' means, how errors are handled, what formats are supported, or any limitations. The agent would have to guess about important behavioral aspects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description doesn't add any parameter information beyond what's already in the schema (which has 100% coverage). The schema fully documents the single 'url' parameter, so the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('fetches') and resource ('a website'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'mood' (which appears unrelated), so it doesn't fully achieve sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives or any contextual prerequisites. It simply states what the tool does without indicating appropriate use cases or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

moodA

Ask the server about its mood - it's always happy!

ParametersJSON Schema
NameRequiredDescriptionDefault
questionYesAsk this MCP server about its mood! You can phrase your question in any way you like - 'How are you?', 'What's your mood?', or even 'Are you having a good day?'. The server will always respond with a cheerful message and a heart ❤️

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals key traits: the server will 'always respond with a cheerful message and a heart ❤️' and 'it's always happy!' which discloses predictable behavior. However, it doesn't mention rate limits, authentication needs, or other operational constraints that would be helpful for a complete behavioral picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one sentence) and front-loaded with the core purpose. Every word earns its place - 'Ask the server about its mood' establishes function, and 'it's always happy!' adds useful behavioral context without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (single parameter, no output schema, no annotations), the description provides adequate context. It explains what the tool does and the predictable response behavior. For a straightforward mood inquiry tool, this is reasonably complete, though it could benefit from mentioning the response format more explicitly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents the single 'question' parameter with examples. The description doesn't add any parameter-specific information beyond what's in the schema. This meets the baseline of 3 for high schema coverage where the description doesn't need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Ask the server about its mood' - a specific verb ('Ask') and resource ('server's mood'). It distinguishes from the sibling tool 'mcp_fetch' by focusing on mood inquiry rather than data fetching. However, it doesn't explicitly contrast with the sibling, keeping it at 4 instead of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through 'it's always happy!' which suggests this is for cheerful interactions, but doesn't provide explicit guidance on when to use this versus alternatives. No when-not-to-use scenarios or comparison to sibling tools is mentioned, leaving usage somewhat implied rather than clearly defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation5/5

The two tools have completely distinct purposes: one fetches website content, while the other returns a static mood response. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool for each task.

Naming Consistency3/5

The tools use different naming conventions: 'mcp_fetch' follows a prefix_verb pattern, while 'mood' is a simple noun. This mixed style lacks a predictable pattern, though both names are readable and descriptive of their functions.

Tool Count2/5

With only two tools, the server feels thin and under-scoped for a template intended for Cursor IDE, which typically involves more complex operations. This minimal set may not adequately cover common IDE-related tasks, suggesting a mismatch in scope.

Completeness2/5

Inferred as a template for IDE integration, the tool surface is severely incomplete. It lacks core functionalities like file manipulation, code analysis, or project management, leaving significant gaps that would hinder agent workflows in an IDE context.

Maintenance

ActivityInactive
ResponsivenessNo issues

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